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Microdata: Making Metadata Matter for Machines

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Microdata: Making Metadata Matter for Machines


Published April 12, 2013


WARNING: you may come away with ideas not only for enriching your library system, but for your web site and other web-based library applications as well!

Microdata enables search engines and other automated processes to make sense of the data on a web page — like identifying the title, author, and identification number of a book from all of the other content on a given page. Web pages enhanced with microdata contribute to the semantic web, and in turn are more likely to be incorporated into search engines and advanced web applications. If it sounds like we should publish microdata from Evergreen’s catalogue, you will be pleased to know that Evergreen was (naturally) the first library system to incorporate microdata in its default public catalogue with the 2.2.0 release in June 2012.

In this session, Dan Scott (the contributor of the schema.org microdata enhancement for Evergreen and a participant in the schemabibex effort to extend schema.org to better support bibliographic data) will discuss the origins of the microdata standards, explain how nominally machine-readable cataloguing data can fit into the machine-actionable semantic web, reflect on the impact that a microdata-enabled catalogue has had at Laurentian University to date, and offer some thoughts about the future of microdata – including the schema.org and RDFa Lite standards.


Producer Scott, Dan
Language English

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